三维隐式向量空间的非刚性配准

Zhi-Quan Cheng, Wei Jiang, Gang Dang, Ralph Robert Martin, Jun Li, Honghua Li, Yin Chen, Yanzhen Wang, Bao Li, Kai Xu, Shiyao Jin
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引用次数: 16

摘要

我们提出了一种隐式方法,用于运动和变形对象的成对非刚性配准。感兴趣的形状隐式嵌入在三维隐式向量空间中。在这个隐式嵌入空间中,使用全局到局部框架执行注册。首先,利用定义在矢量距离函数上的非线性优化函数寻找形状之间的全局对齐;其次,采用增量三次b样条自由变形法恢复非刚性变换参数;用最小化能量泛函的形式提出了局部非刚性配准问题,给出了一个封闭的线性系统,并用改进的迭代高斯-塞德尔方法求解。我们的方法可以持续地产生光滑连续的配准场,并正确地建立密集的一对一对应。通过使用隐式向量表示,它可以自然地处理开放的部分形状和封闭的形状,以及带有间隙和噪声的不完美模型。在多个数据集上的实验结果证明了该方法的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-rigid Registration in 3D Implicit Vector Space
We present an implicit approach for pair-wise non-rigid registration of moving and deforming objects. Shapes of interest are implicitly embedded in the 3D implicit vector space. In this implicit embedding space, registration is performed using a global-to-local framework. Firstly, a non-linear optimization functional defined on the vector distance function is used to find the global alignment between shapes. Secondly, an incremental cubic B-spline free form deformation is used to recover the non-rigid transformation parameters. Local non-rigid registration is posed in terms of minimising an energy functional, for which we give a closed-form linear system and solve it using an improved iterative Gauss-Seidel method. Our approach can consistently produce smooth and continuous registration fields, and correctly establish dense one-to-one correspondences. It can naturally deal with both open partial and closed shapes, and imperfect models with gaps and noise, through its use of the implicit vector representation. Experimental results on several datasets demonstrate the robustness of the proposed method.
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